2017 IEEE Symposium on Computational Intelligence and Data Mining (IEEE CIDM' 17)
IEEE CIDM 2017 organized by the
IEEE Computational Intelligence Society Data Mining Technical Committee
is one of the largest and best attended symposia of the of the IEEE
Symposium Series of Computational Intelligence (IEEE SSCI 2017). IEEE
CIDM 2017 will bring together researchers and practitioners from around
the world to discuss the latest advances in the field of computational
intelligence applied to data mining and will act as a major forum for
the presentation of recent results in theory, algorithms, systems and
applications.
Topics
Topics
related to all aspects of data mining and machine learning, such as
theories, algorithms, systems and applications, particularly those
based on computational intelligence technologies, are welcome; these
include, but are not limited to:
- Neural networks for data mining
- Evolutionary algorithms for data mining
- Fuzzy sets for data mining
- Data mining with soft computing
- Foundations of data mining
- Mining with big data
- Classification, Clustering, Regression
- Association
- Feature learning and feature engineering
- Machine learning algorithms
- Mining from streaming data
- Deep learning
- Data mining from nonstationary and drifting environments
- Multimedia data mining
- Text mining
- Link and graph mining
- Social media mining
- Collaborative filtering
- Crowd sourcing
- Personalization
- Security, privacy and social impact of data mining
- Data mining applications
Accepted
Special Sessions
- Mining the sky: knowledge discovery in big and complex astronomical data sets and data streams
- Organizers:
Erzsébet Merényi, Rice University, Houston, Texas, USA
George Djorgovski, Center for Data-Driven Discovery, Caltech,Pasadena, California, USA
Giuseppe Longo, University Federico II in Napoli (I), Italy
Kai Polsterer, Heidelberg Institute for Theoretical Studies, Germany - More Information
- Computational Intelligence and Financial Engineering: Now and Future
- Organizers:
An-Pin Chen, National Chiao Tung University, HsinChu, Taiwan
Mu-Yen Chen, National Taichung University of Science and Technology, Taiwan - More Information
- Representation learning for transfer and collaborative approaches
- Organizers:
Younès Bennani, Paris 13 University, France
Guénaël Cabanes, Paris 13 University, France
Nistor Grozavu, Paris 13 University, France
Basarab Matei, Paris 13 University, France - More Information
Symposium Co-Chairs
Robi Polikar
Rowan University, Glassboro, NJ 08028, USA
Email: polikar@rowan.edu
Friedhelm Schwenker
Ulm University, Germany
Email: friedhelm.schwenker@uni-ulm.de
Barbara Hammer
Bielefeld University, Germany
Email: bhammer@techfak.uni-bielefeld.de
Gang Li
Daekin University, Melbourne, Australia
Email: gangli@gmail.com
Program
Committee
- Sven F. Crone, UK
- Joao Gama, Portugal
- Will van der Aalst, Austria
- Ahmed Azar, Egypt
- Manuel Roveri, Italy
- Gregory Ditzler, USA
- Nitesh Chawla, USA
- Paula Lisboa, UK
- José D. Martin Guerrero, Spain
- Alfredo Vellido, Spain
- Edwin Lughofer, Austria
- Erzsébet Merényi, USA
- Yonghong Peng, UK, Big Data
- Lipo Wang, Singapore
- Guandong Xu, Australia - EDM
- Yang Yu, China
- Giacomo Borachhi, Italy
- Ata Kaban, UK
- Mengjie Zhang, China
- Sanaz Mostaghim, Germany
- Seiichi Ozawa, Japan
- Sansanee Auephanwiriyakul, Thailand
- Kai Qin, Australia
- Mengjie Zhang, New Zealand
- Heli Koskimaki, Finland
- Frank-Michael Schleif, Germany